Artificial Vision Systems for Robotics

Dear Colleagues,

Artificial vision systems are playing an increasingly vital role in advancing robotic technologies. By enabling machines to interpret and understand their surroundings through visual data, artificial vision serves as a fundamental building block for intelligent behaviour in autonomous and semi-autonomous systems. This fusion of vision and robotics is redefining the way robots perceive and interact with the world, moving beyond scripted, rigid behaviours toward more adaptive, responsive, and context-aware operation.

In recent years, significant advancements in computer vision, deep learning, and real-time image processing have expanded the capabilities of robots across a range of applications. From autonomous navigation in dynamic environments to precise object manipulation in industrial settings, vision systems are empowering robots to perform increasingly complex tasks with high accuracy and flexibility. In parallel, multimodal sensing and visually based human–robot interaction is gaining momentum, enabling safer and more intuitive collaboration between humans and machines.

This Special Issue aims to highlight cutting-edge research and practical innovations at the intersection of vision and robotics. It seeks to bring together contributions that explore both foundational techniques and application-driven advancements in this rapidly evolving field. Emphasis is placed on how artificial vision enhances robotic perception, control, autonomy, and adaptability in real-world scenarios.

We invite original research articles, comprehensive reviews, and case studies that address (but are not limited to) the following topics:

• Visual perception and semantic scene understanding for robotic systems;
• Object detection, recognition, segmentation, and tracking using vision-based approaches;
• Vision-guided manipulation and robotic grasping;
• Visual servoing, motion estimation, and closed-loop control;
• Three-dimensional vision, depth sensing, and SLAM (Simultaneous Localization and Mapping);
• Deep learning and AI techniques for robotic vision;
• Sensor fusion and integration of multi-modal data (e.g., LiDAR, RGB-D, thermal);
• Human detection, gesture recognition, and visual interfaces for human–robot interaction;
• Vision-enabled robotic applications in autonomous driving, smart manufacturing, healthcare, agriculture, and search-and-rescue operations.

Contributions that introduce novel algorithms, demonstrate performance in realistic or challenging conditions, or provide publicly available datasets, source code, or tools that benefit the research community are especially encouraged.

Dr. Konstantinos Tsintotas
Dr. Ioannis Kostavelis
Dr. Kyriakos Tsiakmakis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Robotics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• visual perception
• semantic scene understanding
• object detection
• vision-guided manipulation
• robotic grasping
• visual servoing
• motion estimation
• closed-loop control
• three-dimensional vision
• SLAM (Simultaneous Localization and Mapping)
• deep learning and AI for robotic vision
• sensor fusion
• vision-enabled robotic applications